code: def weights_init_normal(m):
      classname = m.__class__.__name__
      if classname.find("Conv") != -1:
          m.weight.data.normal_(0.0, 0.02)
      elif classname.find("BatchNorm") != -1:
          m.weight.data.normal_(1.0, 0.02)
          m.bias.data.fill_(0)
  
file_path: gans-with-pytorch/ralsgan/ralsgan.py
imports: import argparse
  import numpy
  import torch
  from torch import nn, optim
  from torch.autograd.variable import Variable
  from torchvision import transforms, datasets
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: weights_init_normal(m) without return types